Why Optimize?

Your researchers are your most valuable machine learning asset and will be responsible for developing the differentiated models that create the most value for your business. And experts who automate hyperparameter optimization develop high-performing models at a faster rate. Maximize the productivity of your experts with SigOpt’s black-box optimization solution and realize the full potential of your machine learning investment.

Solutions

$13 Trillion in Global AI Value

Growing pressure on the enterprise to earn a return from their machine learning investment

79% Fear AI Competition

Executives consider AI-enabled new entrants their single biggest threat

10x Growth in Demand for Talent

Competition over machine learning talent places a premium on productivity

Growing pressure to deliver AI results

As AI expectations soar, so does the pressure on companies to realize economic value from their machine learning investments. This pressure places a premium on researchers capable of developing differentiated models for each particular business need. Performance often determines whether these differentiated models make it into production, and model optimization often plays a significant role in this process.

AI threatens to disrupt industries

Competition from AI-first companies compounds the pressure on executives to realize this AI impact on an even faster timeline. Modeling is the next wave of innovation that threatens to “eat the world” and reshape trillion-dollar industries in the process. Without investment in researchers and tools that augment them, incumbents risk losing to new entrants who do.

Improving productivity is at a premium

Although the supply of machine learning engineers is exploding, it still cannot keep pace with demand. This puts pressure on companies to augment each of their researchers as much as possible to realize their full machine learning potential. To attract and retain this level of talent, teams are investing in best-in-class tools so they have the best possible research environment. And they are automating key parts of the process like model optimization so their teams are as productive as possible.

$13 Trillion in Global AI Value

Growing pressure on the enterprise to earn a return from their machine learning investment

Growing pressure to deliver AI results

As AI expectations soar, so does the pressure on companies to realize economic value from their machine learning investments. This pressure places a premium on researchers capable of developing differentiated models for each particular business need. Performance often determines whether these differentiated models make it into production, and model optimization often plays a significant role in this process.

79% Fear AI Competition

Executives consider AI-enabled new entrants their single biggest threat

AI threatens to disrupt industries

Competition from AI-first companies compounds the pressure on executives to realize this AI impact on an even faster timeline. Modeling is the next wave of innovation that threatens to “eat the world” and reshape trillion-dollar industries in the process. Without investment in researchers and tools that augment them, incumbents risk losing to new entrants who do.

10x Growth in Demand for Talent

Competition over machine learning talent places a premium on productivity

Improving productivity is at a premium

Although the supply of machine learning engineers is exploding, it still cannot keep pace with demand. This puts pressure on companies to augment each of their researchers as much as possible to realize their full machine learning potential. To attract and retain this level of talent, teams are investing in best-in-class tools so they have the best possible research environment. And they are automating key parts of the process like model optimization so their teams are as productive as possible.

Rely on a Solution Built for the Enterprise

Modular

SigOpt is easy to embed in any machine learning platform with a few lines of code. We are built to fit into your workflow, regardless of how you design it today or change it tomorrow.

Proven

Augment your experts with model optimization so they can develop high-performing models at a much faster rate.

Scalable

Automate optimization for any model with our API-enabled solution, whether the model has 100 hyperparameters, requires 100x parallelism to tune or can benefit from advanced optimization techniques like multimetric or multitask.

Outperform Other Optimizers

Accelerate Wall-Clock Time to Tune

SigOpt’s proprietary solution efficiently explores and exploits your search space to uncover the global optima for any model much faster than grid search, random search or open source Bayesian optimization.

Increase Computational Efficiency

Tune models with a computationally efficient optimization solution and maximizes the utilization of your clusters. This process is critical to scaling machine learning in production.

Improve Model Performance

While there is no free lunch, SigOpt consistently outperforms other optimizers across any variety of models that your team develops to solve different business challenges.

Earn a Return on your Machine Learning

Augment Expert Productivity

“We can keep our experts focused on the tasks core to our business, and entrust the SigOpt platform to find the optimal hyperparameter configurations for our models, irrespective of the data type and model type.”

– Deep Learning Engineer

Model-Training-Tuning

Amplify Impact of Your Models

“SigOpt has helped us solve an optimization problem that was too challenging for traditional approaches. SigOpt has powered a marketing allocation simulator in a way that has given both and our client a competitive advantage.”

– Head of Data Science

Production-and-Deployment

Accelerate Model Development

“SigOpt has a highly effective product that we’ve used in a variety of ways to enhance our workflow and research pipeline.”

SigOpt for Enterprise

SigOpt is carefully designed with our enterprise customers in mind. We built an API-enabled user experience that fits into your existing workflow so you can continue to optimize models using our solution regardless of how your infrastructure, stack, team, or workflow evolves over time. Our black-box Optimization Engine is enhanced with applied optimization techniques to meet your evolving model tuning needs. And our Experiment Insights dashboard empowers your researchers to introspect and reproduce experiments through the model development process.

Algo_Trading

Algorithmic Trading

Unlock new trading strategies with advanced optimization techniques for model pipelines and backtests.

SigOpt for Academia

SigOpt’s mission is to empower the world’s experts. To fulfill this mission, we provide a free version of our solution to academics who have encountered the painful process of tackling hyperparameter tuning with manual, grid, random, or open source Bayesian techniques.

Interested in SigOpt by Model Type?

As a black-box optimization solution, SigOpt tunes any model’s hyperparameters without touching the underlying data or model. Our customers have used us on a wide variety of model and problem types, but the categories below represent a few of the most common modeling use cases for which we have developed unique features.

Machine_Learning

Machine Learning

SigOpt is easy to embed in any modeling pipeline to optimize any variety, volume or complexity of machine learning models. This approach ensures your machine learning pipelines will be optimized even as you evolve your infrastructure and workflow.

Nuero_Network

Deep Learning

SigOpt enables even the most complex models with up to 100 hyperparameters and requiring up to 100x parallelism. And our solution includes techniques like Conditional Parameters and Multi-task Optimization so that these more expensive functions – and their architecture – can be optimized.

Backtest

Backtest & Simulations

SigOpt works with leading algorithmic traders and government organizations to optimize some of the most complex backtests and simulations in the world that do not benefit from a closed-form optimization solution.